ApoE2 is associated with reduced incidence of Alzheimer?s Disease and with increased longevity. However, possibly adverse effects have also been reported on renal disease and macular degeneration. We hypothesize that the relationships between ApoE2 and age-related phenotypes are influenced by physical and behavioral factors, biochemical markers (biomarker), and genetic variants. Aging is by far the major risk factor for most of chronic diseases. To date, we have discovered many biological pathways of aging that appear to be shared by chronic diseases. Targeting the pathways from ApoE to aging and chronic diseases with consistent effects could result in overall highly favorable clinical outcomes. In this project, we aim to use the existing 500,000 UK Biobank (UKB) participants to identify ApoE2-associated phenotypes and characterize the effects of ApoE variants and their interactions. The UKB sample includes 217,000 subjects aged 60 to 73 at baseline, with 10 years of clinical records follow-up. The identified associations will be investigated for the underlying mechanisms using physical and behavioral factors, pathways associated with ApoE2-interacting genetic variants, and biomarkers that are established risk factors for cardiovascular diseases, cancers, kidney function and other outcomes. The UKB data is the largest data source of its kind, with rich genetic and phenotypic data that includes electronic medical records and will soon include over 30 biomarker assays. This empowers the detection of smaller effect sizes and offers the opportunity of analyzing multiple traits at the same time, in particular searching for gene-environment and gene-gene interactions with ApoE2. We are able to study the roles of environmental factors and biomarkers in the relationships between ApoE2 and age-related phenotypes and conduct a genome-wide gene-gene interaction study to identify ApoE2-interacting variants. These variants will be mapped to genes using both positional and functional information, including eQTL data to investigate the tissue-specific expression profiles for identified variants. Following that, gene-based and pathway (gene- set) analyses will be performed to gain biological insights. Our team has specialties in statistical genetics, genetic epidemiology, bioinformatics, genetics, and clinical geriatrics and includes leaders in this field with experience leading genomic analyses in aging cohorts. The proposed work builds on our recent analysis of parental longevity in UKB, which added 24 new variants to the previously proven associations with ApoE status.1 The long term goal of this project is to clarify positive and negative associations with health outcomes and to understand the relationships between ApoE2 and age-related phenotypes. By integrating the results across age-related phenotypes, we expect to clarify the positive and negative correlates of ApoE2 and identify pathways to target with potential interventions to ultimately promote healthy aging.